EDGE bioinformatics

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Empowering the Development of Genomics Expertise

mission

  • No need for high-level bioinformaticists at the site of sequencing.
  • No need to move large datasets.
  • Edge Bioinformatics enables sequencing as a solution in the biological facilities where human-resources, space, bandwidth, and time are limited
  • A highly adaptable bioinformatics platform that allows laboratories to quickly analyze and interpret genomic sequence data.
  • Allow users to address a wide range of use cases including assay validataion and the characterization of novel biological threats, clinical samples, and complex environmental samples.
Close workflow

Implementation

  • EDGE pipeline was implemented in Perl and wraps up several existing tools within the package including a cutting-edge assembler and sequencing reads aligners.
  • The User Interface was mainly implemented in JQuery Mobile, which is a HTML5-based user interface system designed to make responsive web sites and apps that are accessible on all smartphone, tablet and desktop devices.
  • The current version of EDGE pipeline has been extensively tested on a Linux Server with Ubuntu 13.04 operation system and will only work on 64bit Linux environments.
  • Due to the involvement of several memory/time consuming steps, it requires at least 16Gb memory and at least 8 computing CPUs. A higher computer spec is recommended: 128Gb memory and 16 computing CPUs.

Download & Updates

Please check our GitHub site LANL-Bioinformatics.

Tutorial & Help

The tutorial and guide are hosted in readthedocs.org in online or PDF version. User discussion group will be online soon.

Input Your Sample

EDGE requires sequence data files in FASTQ format. EDGE allows both paired-end and single-end sequences.

Input Raw Reads

Input from NCBI Short Reads Archive(SRA)

Paired-end reads:

file
file Delete

and/or

file Delete

(Internet requried) Input SRA accessions support studies (SRP*/ERP*/DRP*), experiments (SRX*/ERX*/DRX*), samples (SRS*/ERS*/DRS*), runs (SRR*/ERR*/DRR*), or submissions (SRA*/ERA*/DRA*). ex: SRR1553609

| additional options |
Add Paired-end Input Add Single-end Input
file

Your customized parameters can be used again. You can utilize the file selector above to upload a standard config file generated by EDGE bioinformatics.

Batch Project Submission

Run EDGE with Multiple projects using a tools set configuration. Click [Sample Input] to see the example.

or enter your batch sample descriptions here

Choose Processes / Analyses

EDGE provides many modules to do various analyses. You can choose to run or skip a specific process. Parameters/options are provided for most of the analyses. You can click here to turn all on, expand all sections or close all sections.

  1. Quality Trim and Filter
    Run Quality Trim and Filter
    file
  2. Host Removal
    Run Host Removal

    and/or

    file

Bypass assembly and use pre-assembled contigs
file
Assembler

IDBA_UD performs well on isolates as well as metagenomes but it may not work well on very large genomes.

SPAdes performs well on isolates as well as single cell data but it may not work on larger genome, and it takes more computational resource. PacBio CLR and Oxford Nanopore reads are used for gap closure and repeat resolution.

Single Cell Data
file
file
Annotation
Annotation Tool
Specify Kingdom

Please choose the genome type you would like to annotate for Prokka to do genome annotation.

file

Please provide the reference/source annotation (Genbank file), EDGE will use RATT to transfer the annotation from the reference genome. The reference genome must be close relative to the sample.

Given one or multiple reference genome FASTA files, EDGE will turn on the analysis of the reads/contigs mapping to reference and JBrowse reference track generation. Given a reference genome genbank file, EDGE will also turn on variant analysis.

and/or

file
Identify Unmapped Reads
Identify Unmapped Contigs

EDGE will try to classify reads and contigs that are unmapped to references by mapping them to NCBI RefSeq database.

  1. Read-based Taxonomy Classification
  2. EDGE will use all reads by default. You can change the behavior to use reads that are unmapped to the reference if Reference-based Analysis is on.

    Always use all reads

    EDGE uses multiple tools for taxonomy classification including GOTTCHA (bacterial & viral databases), MetaPhlAn, MetaPhyler (short read version), Kraken, MetaScope and reads mapping to NCBI RefSeq using BWA.

    Classification Tools
  3. Contig-based Taxonomy Classification
  4. EDGE will map contigs to NCBI genomes and make taxonomy inference to each contigs.

    Contigs Classification

EDGE supports 5 pre-computed databases for SNP phylogeny analsysis and two tree builders. FastTree is faster and RAxML is slower but more accurate.

Tree Build Method

or

file Add

  1. Primer Validation
    Run Primer Validation

    Given a primer file, EDGE will run validation of the primer pair to the reference and/or assembled contigs, as available.

    file
    Maximum Mismatch
  2. Primer Design
    Run Primer Design

    EDGE will design primers based on the assembled contigs.

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Max file size is 5gb. Allowed File types are fastq, fasta and genbank and can be in gzip format. Files will be kept for 7 days.

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EDGE version 1.1